Biosignals generally refer to detectable signals generated by a living organism, typically a human. The signals may be, for instance, electrical, magnetic, mechanical, acoustical, chemical, or thermal, in nature. In any such cases, an appropriate sensor is used to detect the bio signal of interest and translate that signal into meaningful information about the body (e.g., brain activity, heart activity, eye activity, to name a few examples). Electrical signals generated by the body are typically sensed using an electrode applied to the body near the origin of the electrical signal, such as on the head to detect brain-based signals or on the chest to detect heart-based signals. The electrical signal captured by the electrode may then be amplified to a signal strength suitable for subsequent processing and analysis (e.g., patient diagnosis based on detected signal). Some example use cases where electrical biosignals are monitored include: electroencephalography (EEG) for monitoring electrical brain activity; electrocardiogram (ECG) for monitoring electrical heart activity; electromyogram (EMG) for monitoring electrical muscle activity; and electrooculography (EOG) for monitoring electrical eye activity. Some sensor technology can detect electric biosignals without contacting the body, such as remote sensors for monitoring heart or brain activity of patients who cannot be touched, such as those with sensitive skin or burns. Other non-electrical body signals can be sensed using a transducer that converts the body signal to an electrical signal, such as an acoustic transducer that converts sounds to an electrical signal, or an electrochemical sensor that converts chemical reaction to an electrical signal. The resulting signal can then be amplified and processed. In any such cases, biosignals detection systems can be susceptible to noise. Traditionally, biosignal detection systems such as EEG, ECG or EOG systems utilize software-based artifact (noise) detection algorithms like independent component analysis (ICA) or signal space projection (SSP) for identifying noise artifacts from recorded data and marking relevant epochs as invalid. Thus, an unwanted noise component of the recorded biosignals can be ignored to provide better accuracy. Unfortunately, there are a number of non-trivial issues associated with such noise detection techniques.
These and other features of the present embodiments will be understood better by reading the following detailed description, taken together with the figures herein described. In the drawings, each identical or nearly identical component that is illustrated in various figures may be represented by a like numeral. For purposes of clarity, not every component may be labeled in every drawing.